fixed the RAg in test pipeline issue

app/services/vector_store.py

@@ -1,7 +1,5 @@
 from qdrant_client import QdrantClient, models
-from qdrant_client.http.models import (
-    Distance, VectorParams, PointStruct, Filter, FieldCondition, MatchValue
-)
+from qdrant_client.http.models import Distance, VectorParams, PointStruct
 from app.config import settings
 from typing import List, Dict, Any, Optional
 import logging
@@ -103,15 +101,13 @@ class VectorStoreService:
         collection_name: str,
         query_vector: List[float],
         limit: int = 5,
-        score_threshold: float = 0.3,
     ) -> List[Dict[str, Any]]:
-        """Search for similar vectors"""
+        """Search for similar vectors, returning the top-N by cosine score."""
         try:
             results = self.client.query_points(
                 collection_name=collection_name,
                 query=query_vector,
                 limit=limit,
-                score_threshold=score_threshold,
             ).points
             return [
                 {
@@ -122,7 +118,7 @@ class VectorStoreService:
                 for r in results
             ]
         except Exception as e:
-            logger.error(f"Error searching vectors: {e}")
+            logger.error(f"Error searching vectors in '{collection_name}': {e}", exc_info=True)
             return []
 
     def delete_by_document_id(self, collection_name: str, document_id: str) -> bool:
@@ -131,19 +127,21 @@ class VectorStoreService:
             self.client.delete(
                 collection_name=collection_name,
                 points_selector=models.FilterSelector(
-                    filter=Filter(
+                    filter=models.Filter(
                         must=[
-                            FieldCondition(
+                            models.FieldCondition(
                                 key="document_id",
-                                match=MatchValue(value=document_id),
+                                match=models.MatchValue(value=document_id),
                             )
                         ]
                     )
                 ),
+                wait=True,
             )
+            logger.info(f"Deleted vectors for document '{document_id}' from '{collection_name}'")
             return True
         except Exception as e:
-            logger.error(f"Error deleting document vectors: {e}")
+            logger.error(f"Error deleting vectors for document '{document_id}' in '{collection_name}': {e}", exc_info=True)
             return False
 
     def count_vectors(self, collection_name: str) -> int: